Andrew Hong, Luis Aragon
August 2018
To view the project, please refer to the FinalProject.pdf file for the written summary, code output, and appendix. For a closer look at each step of the code, refer to the Project.md file.
The World Happiness Report is a survey that ranks 155 countries based on their happiness. The score is calculated by asking people the question of how happy they are on a scale of 1-10. This data set contains information from the 2015 survey including factors such as each country’s average happiness score, GDP per capita, average life expectancy, freedom index, etc. Our first question involves using the survey factors to quantitatively understand the effect they have on the response (happiness score) by building and choosing the best model and also seeing if the GDP per capita has interaction with any other variable. Our second question involves using the previous model to predict the happiness scores for hypothetical countries with minimal, average, and maximum variable values.
- Which is the best set of predictors for performing linear regression and predicting happiness score? Does the effect of GDP per capita on Happiness Score depend on any other predictors (Are there interaction terms involving Economy/GDP)?
- What happiness score would a country with minimum, average, or maximum values on all predictors have?
RStudio: R and RMarkdown